Dynamic Stack Using Resizable Array in DSA Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a dynamic stack using a resizable array?

A dynamic stack using a resizable array is a stack data structure that grows or shrinks its underlying array automatically when elements are pushed or popped, so it can handle any number of elements without fixed size limits.

beginner

Why do we resize the array in a dynamic stack?

We resize the array to save memory and allow the stack to grow beyond its initial capacity. When the array is full, we create a bigger array and copy elements. When the stack is mostly empty, we shrink the array to avoid wasting space.

intermediate

What happens when you push an element and the array is full?

When pushing and the array is full, the stack doubles the size of the array, copies all elements to the new array, then adds the new element. This ensures there is always space for new elements.

intermediate

How does popping elements affect the size of the array?

When popping elements, if the number of elements becomes less than a quarter of the array size, the stack shrinks the array to half its current size to save memory.

intermediate

What is the time complexity of push and pop operations in a dynamic stack using a resizable array?

Push and pop operations are usually O(1) (constant time). Occasionally, resizing takes O(n) time, but amortized over many operations, the average time remains O(1).

What triggers the resizing of the array in a dynamic stack?

A Only when the array is full

B When the array is full or less than a quarter full

C Only when the array is empty

D When the array is half full

The array resizes by growing when full and shrinking when less than a quarter full.

What is the initial size of the array in a dynamic stack?

A It can be any fixed size, often small like 1 or 2

B Always 100

C Always 0

D It must be very large to avoid resizing

The initial size is usually small and grows dynamically as needed.

What is the main advantage of using a dynamic stack over a fixed-size stack?

A It is faster for all operations

B It uses less memory always

C It can handle any number of elements without overflow

D It never needs resizing

Dynamic stacks grow as needed, so they avoid overflow errors.

Which operation might take longer than O(1) time in a dynamic stack?

A Resizing the array during push or pop

B Simple push without resizing

C Simple pop without resizing

D Checking if the stack is empty

Resizing requires copying elements, which takes O(n) time.

What happens if you pop from an empty dynamic stack?

A It returns a default value

B The stack resizes automatically

C Nothing happens

D An error or exception occurs

Popping from an empty stack is invalid and usually causes an error.

Explain how a dynamic stack using a resizable array manages memory when pushing and popping elements.

Think about when and why the array size changes.

Describe the time complexity of push and pop operations in a dynamic stack and why resizing does not make them slow on average.

Consider how often resizing occurs compared to normal operations.

Practice

1. What is the main advantage of using a dynamic stack implemented with a resizable array over a fixed-size array stack?

easy

A. It always has a fixed capacity.

B. It uses less memory than a linked list stack.

C. It does not require resizing when full.

D. It can grow or shrink automatically as elements are pushed or popped.

Solution

1. Step 1: Understand fixed-size array stack limitation

   A fixed-size array stack has a set capacity and cannot grow beyond it, causing overflow if exceeded.

2. Step 2: Analyze dynamic stack behavior

   A dynamic stack using a resizable array automatically increases or decreases its size when needed, avoiding overflow and wasted space.

3. Final Answer:

   It can grow or shrink automatically as elements are pushed or popped. -> Option D

4. Quick Check:

   Dynamic resizing = automatic growth/shrink [OK]

Hint: Dynamic stacks resize arrays automatically when full or empty [OK]

Common Mistakes:

• Thinking dynamic stack never resizes
• Confusing dynamic stack with linked list stack
• Assuming fixed capacity for dynamic stack

2. Which of the following is the correct way to double the size of the internal array in a dynamic stack implemented in Python?

easy

A. self.array.extend([None] * len(self.array))

B. self.array = self.array * 2

C. self.array = [None] * (len(self.array) * 2)

D. self.array.append(self.array)

Solution

1. Step 1: Understand array resizing in Python list

   To double the size, we add extra None elements equal to current length to the list.

2. Step 2: Check each option

   self.array.extend([None] * len(self.array)) correctly extends the list by adding None elements equal to current length, doubling size.

3. Final Answer:

   self.array.extend([None] * len(self.array)) -> Option A

4. Quick Check:

   Extend with None * current length = double size [OK]

Hint: Use extend with None times current length to double array [OK]

Common Mistakes:

• Using multiplication on list copies elements, not size
• Assigning new list loses old elements
• Appending array inside itself causes nested list

3. Consider this Python code for a dynamic stack push operation:

def push(self, item):
    if self.top == len(self.array):
        self.array.extend([None] * len(self.array))
    self.array[self.top] = item
    self.top += 1

stack = DynamicStack()
stack.push(10)
stack.push(20)
stack.push(30)
print(stack.array[:stack.top])

What will be the printed output?

medium

A. [10, 20, 30]

B. [10, 20, 30, None, None, None]

C. [None, None, None]

D. IndexError

Solution

1. Step 1: Trace push calls and array state

   Initially array is empty or small. On first push, item 10 is placed at index 0, top becomes 1. Similarly for 20 and 30 at indices 1 and 2.

2. Step 2: Print array slice up to top

   Printing array[:top] shows only elements at indices 0,1,2 which are [10, 20, 30].

3. Final Answer:

   [10, 20, 30] -> Option A

4. Quick Check:

   Print array slice up to top = pushed elements [OK]

Hint: Print only up to top index to see current stack elements [OK]

Common Mistakes:

• Printing full array including None values
• Confusing top index with length
• Expecting error due to resizing

4. Given this buggy pop method for a dynamic stack:

def pop(self):
    if self.top == 0:
        return None
    self.top -= 1
    item = self.array[self.top]
    self.array[self.top] = None
    if self.top < len(self.array) // 4:
        self.array = self.array[:len(self.array) // 2]
    return item

What is the main issue with this code?

medium

A. It does not set popped element to None.

B. It does not check for empty stack before popping.

C. It shrinks the array too early, causing frequent resizing.

D. It doubles the array size instead of shrinking.

Solution

1. Step 1: Understand shrinking condition

   The array shrinks when top is less than one-fourth of array length, which can cause frequent resizing if elements fluctuate near this threshold.

2. Step 2: Identify problem with frequent resizing

   Frequent shrinking and expanding wastes time and resources, so better to shrink less aggressively.

3. Final Answer:

   It shrinks the array too early, causing frequent resizing. -> Option C

4. Quick Check:

   Shrink threshold too high = frequent resize [OK]

Hint: Shrink array only when usage is very low to avoid thrashing [OK]

Common Mistakes:

• Ignoring empty stack check (it is present)
• Confusing shrinking with doubling
• Not clearing popped element

5. You want to implement a dynamic stack that minimizes memory usage by shrinking the internal array only when the number of elements is less than 1/8 of the array size. Which change should you make to the pop method's shrinking condition?

def pop(self):
    if self.top == 0:
        return None
    self.top -= 1
    item = self.array[self.top]
    self.array[self.top] = None
    if ???:
        self.array = self.array[:len(self.array) // 2]
    return item

hard

A. if self.top == 0

B. if self.top < len(self.array) // 8

C. if self.top <= len(self.array) // 2

D. if self.top < len(self.array) // 4

Solution

1. Step 1: Understand shrinking threshold

   To shrink only when usage is less than 1/8, the condition must check if top is less than array length divided by 8.

2. Step 2: Match condition to code

   if self.top < len(self.array) // 8 correctly uses 'if self.top < len(self.array) // 8' to trigger shrinking at 1/8 usage.

3. Final Answer:

   if self.top < len(self.array) // 8 -> Option B

4. Quick Check:

   Shrink when usage < 1/8 = condition in if self.top < len(self.array) // 8 [OK]

Hint: Use 1/8 threshold to shrink less often and save memory [OK]

Common Mistakes:

• Using 1/4 threshold shrinks too early
• Using equality instead of less than
• Shrinking when stack is empty only